Previous expert systems (particularly in medicine) have been used to supply the user with online/automated facility where a diagnostic determination is aided by a monolithic and sophisticated algorithm using expert rules and inference engines. What makes these “all encompassing” expert systems unmanageable relates to the difficulty in validating and updating new rules within the framework of a large expert system.
In the practice of medicine, all the references that clinicians use to help make their diagnosis and treatment plans must be validated. Large expert systems are difficult to design for any utility for the physician due to the inverse relationship between complexity of algorithms and testability. In order for expert systems to properly assist its human user, there must be a large degree of completeness/thoroughness. However, making sure all the rules embedded in such software are accurate would be a large undertaking particularly when you begin to add and modify new rules over time as there are developments in the field. An expert system is only useful if the algorithms contained in such a system are current (embedding the latest and more relevant information available).